Articles | Volume 12, issue 21
https://doi.org/10.5194/bg-12-6463-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/bg-12-6463-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
12 Nov 2015
Research article |
| 12 Nov 2015
Representing northern peatland microtopography and hydrology within the Community Land Model
Climate Change Science Institute and Environmental Sciences Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA
Climate Change Science Institute and Environmental Sciences Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA
D. M. Ricciuto
Climate Change Science Institute and Environmental Sciences Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA
P. J. Hanson
Climate Change Science Institute and Environmental Sciences Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA
Climate Change Science Institute and Environmental Sciences Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA
S. D. Sebestyen
Northern Research Station, USDA Forest Service, Grand Rapids, Minnesota 55744, USA
N. A. Griffiths
Climate Change Science Institute and Environmental Sciences Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA
Climate and Ecosystem Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA
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We developed seven global soil moisture datasets (1970–2016, monthly, half-degree, and multilayer) by merging a wide range of data sources, including in situ and satellite observations, reanalysis, offline land surface model simulations, and Earth system model simulations. Given the great value of long-term, multilayer, gap-free soil moisture products to climate research and applications, we believe this paper and the presented datasets would be of interest to many different communities.
Xin Huang, Dan Lu, Daniel M. Ricciuto, Paul J. Hanson, Andrew D. Richardson, Xuehe Lu, Ensheng Weng, Sheng Nie, Lifen Jiang, Enqing Hou, Igor F. Steinmacher, and Yiqi Luo
Geosci. Model Dev., 14, 5217–5238, https://doi.org/10.5194/gmd-14-5217-2021, https://doi.org/10.5194/gmd-14-5217-2021, 2021
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In the data-rich era, data assimilation is widely used to integrate abundant observations into models to reduce uncertainty in ecological forecasting. However, applications of data assimilation are restricted by highly technical requirements. To alleviate this technical burden, we developed a model-independent data assimilation (MIDA) module which is friendly to ecologists with limited programming skills. MIDA also supports a flexible switch of different models or observations in DA analysis.
Eva Sinha, Kate Calvin, Ben Bond-Lamberty, Beth Drewniak, Dan Ricciuto, Khachik Sargsyan, Yanyan Cheng, Carl Bernacchi, and Caitlin Moore
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2021-244, https://doi.org/10.5194/gmd-2021-244, 2021
Preprint withdrawn
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Perennial bioenergy crops are not well represented in global land models, despite projected increase in their production. Our study expands Energy Exascale Earth System Model (E3SM) Land Model (ELM) to include perennial bioenergy crops and calibrates the model for miscanthus and switchgrass. The calibrated model captures the seasonality and magnitude of carbon and energy fluxes. This study provides the foundation for future research examining the impact of perennial bioenergy crop expansion.
Daniel M. Ricciuto, Xiaojuan Yang, Dali Wang, and Peter E. Thornton
Biogeosciences Discuss., https://doi.org/10.5194/bg-2021-163, https://doi.org/10.5194/bg-2021-163, 2021
Publication in BG not foreseen
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This paper uses a novel approach to quantify the impacts of the choice of decomposition model on carbon and nitrogen cycling. We compare the models to experimental data that examined litter decomposition over five different biomes. Despite widely differing assumptions, the models produce similar patterns of decomposition when nutrients are limiting. This differs from past analyses that did not consider the impacts of changing environmental conditions or nutrients.
Claudia Tebaldi, Kevin Debeire, Veronika Eyring, Erich Fischer, John Fyfe, Pierre Friedlingstein, Reto Knutti, Jason Lowe, Brian O'Neill, Benjamin Sanderson, Detlef van Vuuren, Keywan Riahi, Malte Meinshausen, Zebedee Nicholls, Katarzyna B. Tokarska, George Hurtt, Elmar Kriegler, Jean-Francois Lamarque, Gerald Meehl, Richard Moss, Susanne E. Bauer, Olivier Boucher, Victor Brovkin, Young-Hwa Byun, Martin Dix, Silvio Gualdi, Huan Guo, Jasmin G. John, Slava Kharin, YoungHo Kim, Tsuyoshi Koshiro, Libin Ma, Dirk Olivié, Swapna Panickal, Fangli Qiao, Xinyao Rong, Nan Rosenbloom, Martin Schupfner, Roland Séférian, Alistair Sellar, Tido Semmler, Xiaoying Shi, Zhenya Song, Christian Steger, Ronald Stouffer, Neil Swart, Kaoru Tachiiri, Qi Tang, Hiroaki Tatebe, Aurore Voldoire, Evgeny Volodin, Klaus Wyser, Xiaoge Xin, Shuting Yang, Yongqiang Yu, and Tilo Ziehn
Earth Syst. Dynam., 12, 253–293, https://doi.org/10.5194/esd-12-253-2021, https://doi.org/10.5194/esd-12-253-2021, 2021
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We present an overview of CMIP6 ScenarioMIP outcomes from up to 38 participating ESMs according to the new SSP-based scenarios. Average temperature and precipitation projections according to a wide range of forcings, spanning a wider range than the CMIP5 projections, are documented as global averages and geographic patterns. Times of crossing various warming levels are computed, together with benefits of mitigation for selected pairs of scenarios. Comparisons with CMIP5 are also discussed.
Xiaoying Shi, Daniel M. Ricciuto, Peter E. Thornton, Xiaofeng Xu, Fengming Yuan, Richard J. Norby, Anthony P. Walker, Jeffrey M. Warren, Jiafu Mao, Paul J. Hanson, Lin Meng, David Weston, and Natalie A. Griffiths
Biogeosciences, 18, 467–486, https://doi.org/10.5194/bg-18-467-2021, https://doi.org/10.5194/bg-18-467-2021, 2021
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The Sphagnum mosses are the important species of a wetland ecosystem. To better represent the peatland ecosystem, we introduced the moss species to the land model component (ELM) of the Energy Exascale Earth System Model (E3SM) by developing water content dynamics and nonvascular photosynthetic processes for moss. We tested the model against field observations and used the model to make projections of the site's carbon cycle under warming and atmospheric CO2 concentration scenarios.
George C. Hurtt, Louise Chini, Ritvik Sahajpal, Steve Frolking, Benjamin L. Bodirsky, Katherine Calvin, Jonathan C. Doelman, Justin Fisk, Shinichiro Fujimori, Kees Klein Goldewijk, Tomoko Hasegawa, Peter Havlik, Andreas Heinimann, Florian Humpenöder, Johan Jungclaus, Jed O. Kaplan, Jennifer Kennedy, Tamás Krisztin, David Lawrence, Peter Lawrence, Lei Ma, Ole Mertz, Julia Pongratz, Alexander Popp, Benjamin Poulter, Keywan Riahi, Elena Shevliakova, Elke Stehfest, Peter Thornton, Francesco N. Tubiello, Detlef P. van Vuuren, and Xin Zhang
Geosci. Model Dev., 13, 5425–5464, https://doi.org/10.5194/gmd-13-5425-2020, https://doi.org/10.5194/gmd-13-5425-2020, 2020
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To estimate the effects of human land use activities on the carbon–climate system, a new set of global gridded land use forcing datasets was developed to link historical land use data to eight future scenarios in a standard format required by climate models. This new generation of land use harmonization (LUH2) includes updated inputs, higher spatial resolution, more detailed land use transitions, and the addition of important agricultural management layers; it will be used for CMIP6 simulations.
Cited articles
Andrus, R., Wagner, D. J., and Titus, J. E.: Vertical distribution of Sphagnum mosses along hummock-hollow gradient, Can. J. Botany, 61, 3128–3139, 1983.
Bohn, T. J., Podest, E., Schroeder, R., Pinto, N., McDonald, K. C., Glagolev, M., Filippov, I., Maksyutov, S., Heimann, M., Chen, X., and Lettenmaier, D. P.: Modeling the large-scale effects of surface moisture heterogeneity on wetland carbon fluxes in the West Siberian Lowland, Biogeosciences, 10, 6559–6576, https://doi.org/10.5194/bg-10-6559-2013, 2013.
Bond-Lamberty, B., Gower, S. T., and Ahl, D. E.: Improved simulation of poorly drained forests using Biome – BGC, Tree Physiol., 27, 703–715, 2007.
Bridgham, S. D., Megonigal, J. P., Keller, J. K., Bliss, N. B., and Trettin, C.: The carbon balance of North American wetlands, Wetlands, 26, 889–916, 2006.
Brooks, K. N., Verma, S. B., Kim, J., and Verry, E. S.: Scaling up evapotranspiration estimates from process studies to watersheds, in: Peatland biogeochemistry and watershed hydrology at the Marcell Experimental Forest, edited by: Kolka, R. K. Sebestyen, S. D., Verry, E. S., and Brooks, K. N., CRC Press, New York, 177–192, 2011.
Chapin, F. S., Van Cleve, K., and Chapin, M. C.: Soil temperature and nutrient cycling in the tussock growth form of Eriophorum vaginatum, J. Ecol., 67, 169–189, 1979.
Chen, J. M., Chen, X., Ju, W., and Geng, X.: Distributed hydrological model for mapping evapotranspiration using remote sensing inputs, J. Hydrol., 305, 15–39, https://doi.org/10.1016/j.jhydrol.2004.08.029, 2005.
Chen, X., Chen, J. M., An, S., and Ju, W.: Effects of topography on simulated net primary productivity at landscape scale, J. Environ. Manage., 85, 585–596, https://doi.org/10.1016/j.jenvman.2006.04.026, 2007
Couwenberg, J., and Joosten, H.: Self-organization in raised bog patterning: the origin of microtope zonation and mesotope diversity, J. Ecol., 93, 1238–1248, 2005.
Damman, A. W. H.: Distribution and movement of elements in ombrotrophic peat bogs, Oikos, 30, 480–495, 1978.
Dimitrov, D. D., Grant, R. F., Lafleur, P. M., and Humphreys, E. R.: Modeling the effects of hydrology on gross primary productivity and net ecosystem productivity at Mer Bleue bog, J. Geophys. Res., 116, G04010, https://doi.org/10.1029/2010JG001586, 2011.
Dise, N., Shurpali, N. J., Weishampel, P., Verma, S. B., Verry, E. S., Gorham, E., Crill, P. M., Harriss, R. C., Kelley, C. A., Yavitt, J. B., Smemo, K. A., Kolka, R. K., Smith, K., Kim, J., Clement, R. J., Arkebauer, T. J., Bartlett, K. B., Billesbach, D. P., Bridgham, S. D., Elling, A. E., Flebbe, P. A., King, J. Y., Martens, C. S., Sebacher, D. I., Williams, C. J., and Wieder, R. K.: Carbon emissions from peatlands, in Peatland biogeochemistry and watershed hydrology at the Marcell Experimental Forest, edited by: Kolka, R. K., Sebestyen, S. D., Verry, E. S., and Brooks, K. N, CRC Press, New York, 297–-347, 2011.
Eppinga, M. B., de Ruiter, P. C., Wassen, M. J., and Rietkerk, M.: Nutrients and hydrology indicate the driving mechanisms of peatland surface patterning, Am. Nat., 173, 803–818, 2009.
Frolking, S., Roulet, N. T., Moore, T. R., Lafleur, P. M., Bubier, J. L., and Crill, P. M.: Modelling the seasonal to annual carbon balance of Mer Bleue bog, Ontario, Canada, Global Biogeochem. Cy., 16, 1030, https://doi.org/10.1029/2001GB001457, 2002.
Frolking, S., Roulet, N. T., Tuittila, E., Bubier, J. L., Quillet, A., Talbot, J., and Richard, P. J. H.: A new model of Holocene peatland net primary production, decomposition, water balance, and peat accumulation, Earth Syst. Dynam., 1, 1–21, https://doi.org/10.5194/esd-1-1-2010, 2010.
Ge, Y. and Gong, G.: Land surface insulation response to snow depth variability, J. Geophys. Res., 115, D08107, https://doi.org/10.1029/2009JD012798, 2010.
Gorham, E.: Northern peatlands: Role in the carbon cycle and probable responses to climatic warming, Ecol. Appl., 1, 182–195, 1991.
Grant, R. F., Desai, A. R., and Sulman, B. N.: Modelling contrasting responses of wetland productivity to changes in water table depth, Biogeosciences, 9, 4215–4231, https://doi.org/10.5194/bg-9-4215-2012, 2012.
Hanson, P. J., Kenneth, W. C., Wullschleger, S. D., Riggs, J. S., Thomas, W. K., Todd, D. E., and Warren, J. M.: A method for experimental heating of intact soil profiles for application to climate change experiments, Glob. Change Biol., 17, 1083–1096, 2011.
Hilbert, D. W, Roulet, N., and Moore, T. R.: Modelling and analysis of peatlands as dynamical systems, J. Ecol., 88, 230–242, 2000.
Idso, S. B.: A Set of Equations for Full Spectrum and 8- to 14 μm and 10.5- to 12.5 μm Thermal-Radiation from Cloudless Skies, Water Resour. Res., 17, 295–304, 1981.
Ise, T., Dunn, A. L., Wofsy, S. C., and Moorcroft, P. R.: High sensitivity of peat decomposition to climate change through water-table feedback, Nat. Geosci., 1, 763–766, 2008.
Johnson, L. C. and Damman, A. W. H.: Species-controlled Sphagnum decay on a south Swedish raised bog, Oikos, 61, 234–242, 1991.
Ju, W., Chen, J. M., Black, T. A., Barr, A. G., McCaughey, H., and Roulet, N. T.: Hydrological effects on carbon cycles of Canada's forests and wetlands, Tellus, Ser. B, 58, 16–30, https://doi.org/10.1111/j.1600-0889.2005.00168.x, 2006.
Kadlec, R. H. and Knight, R. L.: Treatment Wetlands, second Edn., CRC Press, Boca Raton, Florida, 21–57, 2009.
Kanamitsu, M., Ebisuzaki, W., Woollen, J., Yang, S., Hnilo, J. J., Fiorino, M., and Potter, G. L.: NCEP–DOE AMIP-II Reanalysis (R-2), B. Am. Meteorol. Soc., 83, 1631–1643, 2002.
Kazezyılmaz-Alhan, C. M., Medina Jr., M. A., and Richardson, C. J.: A wetland hydrology and water quality model incorporating surface water/groundwater interactions, Water Resour. Res., 43, W04434, https://doi.org/10.1029/2006WR005003, 2007.
Koven, C. D., Riley, W. J., Subin, Z. M., Tang, J. Y., Torn, M. S., Collins, W. D., Bonan, G. B., Lawrence, D. M., and Swenson, S. C.: The effect of vertically resolved soil biogeochemistry and alternate soil C and N models on C dynamics of CLM4, Biogeosciences, 10, 7109–7131, https://doi.org/10.5194/bg-10-7109-2013, 2013.
Lafleur, P. M., McCaughey, J. H., Joiner, D. W., Bartlett, P. A., and Jelinski, D. E.: Seasonal trends in energy, water, and carbon dioxide fluxes at a northern boreal wetland, J. Geophys. Res., 102, 29009–29020, https://doi.org/10.1029/96JD03326, 1997.
Lafleur, P. M., Roulet, N. T., Bubier, J. L., Frolking, S., and Moore, T.: Interannual variability in the peatland-atmosphere carbon dioxide exchange at an ombrotrophic bog, Global Biogeochem. Cy., 17, 1036, https://doi.org/10.1029/2002GB001983, 2003.
Lawrence, D. M. and Slater, A. G.: Incorporating organic soil into a global climate model, Clim. Dynam., 30, 145–160, https://doi.org/10.1007/s00382-007-0278-1, 2007.
Li, H., Huang, M., Wigmosta, M. S., Ke, Y., Coleman, A. M., Leung, L. R., Wang, A., and Ricciuto, D. M.: Evaluating runoff simulations from the community Land Model 4.0 using observations from flux towers and a mountainous watershed, J. Geophys. Res., 116, D24120. https://doi.org/10.1029/2011JD016276, 2011.
Limpens, J., Berendse, F., Blodau, C., Canadell, J. G., Freeman, C., Holden, J., Roulet, N., Rydin, H., and Schaepman-Strub, G.: Peatlands and the carbon cycle: from local processes to global implications – a synthesis, Biogeosciences, 5, 1475–1491, https://doi.org/10.5194/bg-5-1475-2008, 2008.
Lindholm, T. and Markkula, I.: Moisture conditions in hummocks and hollows in virgin and drained sites on the raised bog Laaviosuo, Southern Finland, Ann. Bot. Fenn., 21, 241–255, 1984.
MacDonald, S. E. and Yin, F.: Factors influencing size inequality in peatland black spruce and tamarack evidence from post drainage release growth, J. Ecol., 87, 404–412, 1999.
Mezbahuddin, M., Grant, R. F., and Hirano, T.: Modelling effects of seasonal variation in water table depth on ecosystem CO2 exchange of a tropical peatland, Biogeosciences, 11, 577–599, https://doi.org/10.5194/bg-11-577-2014, 2014.
Moore, J. K., Lindsay, K., Doney, S. C., Long, M. C., and Misumi, K.: Marine Ecosystem Dynamics and Biogeochemical Cycling in the Community Earth System Model [CESM1(BGC)]: Comparison of the 1990s with the 2090s under the RCP4.5 and RCP8.5 Scenarios, J. Climate, 26, 9291–9312, 2013.
Moore, K. E., Fitzjarrald, D. R., Wofsy, S. C., Daube, B. C., Munger, J. W., Bakwin, P. S., and Crill, P.: A season of heat, water vapor, total hydrocarbon, and ozone fluxes at a subarctic fen, J. Geophys. Res., 99, 1937–1952, https://doi.org/10.1029/93JD01442, 1994.
Moore, T. R.: Growth and net production of Sphagnum at five fen sites, subarctic eastern Canada, Can. J. Bot. 67, 1203–1207, 1989.
Morris, P. J., Baird, A. J., and Belyea, L. R.: The role of hydrological transience in peatland pattern formation, Earth Surface Dynamics, 1, 29–43, 2013.
Nichols, D. S.: Temperature of upland and peatland soils in a north central Minnesota forest, Canadian J. Soil Sci., 78, 493–509, 1998.
Nichols, D. S. and Verry, E. S.: Stream flow and ground water recharge from small forested watersheds in north central Minnesota, J. Hydrol., 245, 89–103, 2001.
Niu, G., Yang, Z., Dickinson, R. E., and Gulden, L. E.: A simple TOPMODEL-based runoff parameterization (SIMTOP) for use in global climate model, J. Geophys. Res., 110, D21106, https://doi.org/10.1029/2005JD006111, 2005.
Nungesser, M. K.: Modelling mircrotopography in boreal peatlands: hummocks and hollows, Ecol. Modell., 165, 175–207, 2003.
Oechel, W. C. and Van Cleve, K.: The role of bryophytes in nutrient cycling in the taiga, in Ecological Studies, Vol. 57, Forest Ecosystems in the Alaskan Taiga, edited by: Van Cleve, K., Chapin III, F. S., Flanagan, P. W., Viereck, L. A., and Dyrness, C. T., Springer-Verlag, New York, 121–137, 1986.
Oleson, K. W., Niu, G., Yang, Z., Lawrence, D. W., Thornton, P. E., Lawrence, P. J., Stöckli, R., Dickinson, R. E., Bonan, G. B., Levis, S., Dai, A., and Qian, T.: Improvements to the Community Land Model and their impact on the hydrological cycle, J. Geophys. Res., 113, G01021, https://doi.org/10.1029/2007JG000563, 2008.
Oleson, K. W., Lawrence, D. W., Bonan, G. B., Drewniak, B., Huang, M., Koven, C. D., Levis, S., Li, F., Riley, W. J., Subin, Z. M., Swenson, S. C., Thornton, P. E., Bozbiyik, A., Fisher, R., Heald, C. L., Kluzek, E., Lamarque, J., Lawrence, P. J., Leung, L. R., Lipscomb, W., Muszala, S., Ricciuto, D. M., Sacks, W., Sun, Y., Tang, J., and Yang, Z.: Technical description of version 4.5 of the Community Land Model (CLM), NCAR/TN-503+STR, NCAR Technical Note, 2013.
Painter, S. L. and Karra, S.: Constitutive model for unfrozen water content in subfreezing unsaturated soils, Vadose Zone J., 13, 1–8, https://doi.org/10.2136/vzj2013.04.0071, 2014.
Painter, S. L., Moulton, J. D., and Wilson, C. J.: Modeling challenges for predicting hydrologic response to degrading permafrost, Hydrogeol. J., 21, 221–224, https://doi.org/10.1007/s10040-012-0917-4, 2013.
Parsekian, A. D., Slater, L., Ntarlagiannis, D., Nolan, J., Sebestyen, S. D., Kolka, R. K., and Hanson, P. J.: Uncertainty in peat volume and soil carbon estimated using ground-penetrating radar and probing, Soil Sci. Soc. Am. J., 76, 1911–1918. https://doi.org/10.2136/sssaj2012.0040, 2012.
Richardson, M. C., Mitchell, C. P. J., Branfireun, B. A., and Kolka, R. K.: Analysis of airborne LiDAR surveys to quantify the characteristic morphologies of northern forested wetlands, J. Geophys. Res., 115, G03005, https://doi.org/10.1029/2009jg000972, 2010.
Riley, W. J., Subin, Z. M., Lawrence, D. M., Swenson, S. C., Torn, M. S., Meng, L., Mahowald, N. M., and Hess, P.: Barriers to predicting changes in global terrestrial methane fluxes: analyses using CLM4Me, a methane biogeochemistry model integrated in CESM, Biogeosciences, 8, 1925–1953, https://doi.org/10.5194/bg-8-1925-2011, 2011.
Robreck, B. J. M., Schouten, M. G. C., Limpens, J., Berendse, F., and Poorter, H.: Interactive effects of water table and precipitation on net CO2 assimilation of three co-occurring Sphagnum mosses differing in distribution above the water table, Glob. Change Biol., 15, 680–691, 2009.
Sebestyen, S. D., Dorrance, C., Olson, D. M., Verry, E. S., Kolka, R. K., Elling, A. E., and Kyllander, R.: Long-term monitoring sites and trends at the Marcell Experimental Forest, in Peatland biogeochemistry and watershed hydrology at the Marcell Experimental Forest, edited by: Kolka, R. K. Sebestyen, S. D., Verry, E. S., and Brooks, K. N., CRC Press, New York, 15–71, 2011a.
Sebestyen, S. D., Verry, E. S., and Brooks, K. N.: Hydrological responses to forest cover changes on uplands and peatlands, in: Peatland biogeochemistry and watershed hydrology at the Marcell Experimental Forest, edited by: Kolka, R. K. Sebestyen, S. D., Verry, E. S., and Brooks, K. N., CRC Press, New York, 433–458, 2011b.
Silvola, J.: Combined effects of varying water content and CO2 concentration on photosynthesis in Sphagnum fuscum, Holarctic Ecol., 13, 224–228, 1990.
Silvola, J., Alm, J., Ahlholm, U., Nykanen, H., and Martikainen, P. J.: CO2 fluxes from peat in boreal mires under varying temperature and moisture conditions, J. Ecol., 84, 219–228, 1996.
Sonnentag, O., Chen, J. M., Roulet, N. T., Ju, W., and Govind, A.: Spatially explicit simulation of peatland hydrology and carbon dioxide exchange: Influence of mesoscale topography, J. Geophys. Res., 113, G02005, https://doi.org/10.1029/2007JG000605, 2008.
Swanson, D. K. and Grigal, D. F.: A simulation model of mire patterning, Oikos, 53, 309–314, 1988.
Swenson, S. C., Lawrence, D. M., and Lee, H.: Improved simulation of the terrestrial hydrological cycle in permafrost regions by the community Land Model, J. Adv. Model. Earth Syst., 4, M08002, https://doi.org/10.1029/2012MS000165, 2012.
St-Hilaire, F., Wu, J., Roulet, N. T., Frolking, S., Lafleur, P. M., Humphreys, E. R., and Arora, V.: McGill wetland model: evaluation of a peatland carbon simulator developed for global assessments, Biogeosciences, 7, 3517–3530, https://doi.org/10.5194/bg-7-3517-2010, 2010.
Tarnocai, C.: The impact of climate change on Canadian Peatlands, Can. Water Resour. J., 34, 453–466, 2009.
Thomas, P. R. and Yao, X.: Stochastic Ranking for Constrained Evolutionary Optimization, IEEE T. Evolut. Comput., 4, 274–283, 2000.
Turetsky, M. R., Bond-Lamberty, B., Euskirchen, E., Talbot, J., Frolking, S., McGuire, A. D., and Tuittila, E. S.: The resilience and functional role of moss in boreal and arctic ecosystems, New Phytol., 196, 49–67, https://doi.org/10.1111/j.1469-8137.2012.04254.x, 2012.
Verry, E. S.: Microtropography and water table fluctuation in a Sphagnum mire, In Proceedings of the 7th International Peat Congress, Dublin, Ireland, The Irish National Peat Committee/The International Peat Society, 11–31, 1984.
Verry, E. S. and Jansenns, J.: Geology, vegetation, and hydrology of the S2 bog at the MEF: 12,000 years in northern Minnesota, in Peatland biogeochemistry and watershed hydrology at the Marcell Experimental Forest, edited by: Kolka, R. K., Sebestyen, S. D., Verry, E. S., Brooks, K. N., CRC Press, New York, 93–134, 2011.
Verry, E. S., Boelter, D. H., Päivänen, J., Nichols, D. S., Malterer, T. J., and Gafni, A.: Physical properties of organic soils, in Peatland biogeochemistry and watershed hydrology at the Marcell Experimental Forest, edited by: Kolka, R. K., Sebestyen, S. D., Verry, E. S., and Brooks, K. N., CRC Press, New York, 135–176, 2011a.
Verry, E. S., Brooks, K. N., Nichols, D. S., Ferris, D. R., and Sebestyen, S. D.: Watershed hydrology, in: Peatland biogeochemistry and watershed hydrology at the Marcell Experimental Forest, edited by: Kolka, R. K., Sebestyen, S. D., Verry, E. S., Brooks, K. N., 193–212, CRC Press, New York, 2011b.
Verry, E. S., Bay, R. R., and Boelter, D. H.: Establishing the Marcell Experimental Forest: Threads in time, in: Peatland biogeochemistry and watershed hydrology at the Marcell Experimental Forest, edited by: Kolka, R. K., Sebestyen, S. D., Verry, E. S., and Brooks, K. N., CRC Press, New York, 1–13, 2011c.
Waddington, J. M., Rotenberg, P. A., and Warren, F. J.: Peat CO2 production in a natural and cutover peatland: Implications for restoration, Biogeochemistry, 54, 115–130, 2001.
Wania, R., Ross, I., and Prentice, I. C.: Implementation and evaluation of a new methane model within a dynamic global vegetation model: LPJ-WHyMe v1.3.1, Geosci. Model Dev., 3, 565–584, https://doi.org/10.5194/gmd-3-565-2010, 2010.
Williams, T. G. and Flanagan, L. B.: Effect of changes in water content on photosynthesis, transpiration and discrimination against 13CO2 and C18}O^{16 in Pleurozium and Sphagnum, Oecologia, 108, 38–46, 1996.
Wu, J., Roulet, N. T., Sagerfors, J., and Nilsson, M. B.: Simulation of six years of carbon fluxes for a sedge-dominated oligotrophic minerogenic peatland in Northern Sweden using the McGill Wetland Model (MWM), J. Geophys. Res.-Biogeo., 118, 795–807, https://doi.org/10.1002/jgrg.20045, 2013.
Wu, J. B., Kutzbach, L., Jager, D., Wille, C., and Wilmking, M.: Evapotranspiration dynamics in a boreal peatland and its impact on the water and energy balance, J. Geophys. Res, 115, G04038, https://doi.org/10.1029/2009JG001075, 2010.
Zhang, Y., Li, C., Trettin, C. C., Li, H., and Sun, G.: An integrated model of soil, hydrology, and vegetation for carbon dynamics in wetland ecosystems, Global Biogeochem. Cy., 16, 1061, https://doi.org/10.1029/2001GB001838, 2002.
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